Language is arguably humanity’s most consequential invention. Unlike any other species, Homo Sapiens has developed a means by which complicated, abstract plans can be efficiently and effectively transmitted from one mind to the next. Thus, our prehistoric ancestors, in contrast to their natural rivals, could successfully coordinate, say, a large-scale hunt, an attack on a foreign tribe, or even how they wanted to arrange life in increasingly complex social communities.

The advent of ChatGPT and the subsequent release of GPT-4 have brought a wave of publicity to the field of generative AI. Many observers marvel at the levels of “creativity” that the technology has attained seemingly overnight and it’s tempting to get lost in pondering its implications on the future of, say, education, white-collar work, healthcare, or any other sector of the economy that suddenly looks ripe for disruption.

If you’re reading this, the mounting news of apparent breakthroughs in generative AI have surely not passed you by: Tools that can compose music, write code, paint pictures, and genuinely seem to be smart enough to pass various state exams have become publicly (and mostly freely) available in a surprisingly short timespan. This wave of commoditization has also shed the light of public discourse onto debates about AI safety which had, until now, been confined to relatively small, mostly academic circles.

Designing Your Work Life by Bill Burnett and Dave Evans. “F**k this s**t, I’m quitting!” Many of us have played with the thought of making a memorable exit from a job we didn’t enjoy at some point in our careers. I know a few people who actually did (though not with quite such strong language), but unsurprisingly that didn’t end well for any of them.

In many instances software architecture is less a product of deliberate design and more an accidental result of countless interactions between people. Or, as Eric Raymond put it more pointedly: “If you have four groups working on a compiler, you’ll get a 4-pass compiler.” How Do Committees Invent? by Mel Conway. This idea was originally introduced by Mel Conway in his 1967 paper “How Do Committees Invent?

The other day I had a wonderful conversation with a friend and fellow software enthusiast about fairness when it comes to the remuneration of knowledge workers. Both of us have been through various posts in different technology companies, increasingly concerning ourselves with management and leadership as our careers progressed. Our conversation honed in on the following question: Is the way people are payed in our industry today fair? Note that I’m not referring only to software developers here—data scientists, UI experts, DevOps heroes, product managers, and all the others who contribute to successful projects are included as well.